{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8a18c48b",
   "metadata": {},
   "source": [
    "# USS Land Cover Intersect Analysis\n",
    "This workbook performs the analysis to calculate the land cover intersection of existing an predicted sites\n",
    "\n",
    "The first cell imports the necessary libraries and establishes universal variables for graphing and data input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "225d2909",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.04855036414876337\n"
     ]
    }
   ],
   "source": [
    "\n",
    "import pandas as pd\n",
    "import rasterio\n",
    "import numpy as np\n",
    "from rasterstats import zonal_stats\n",
    "import geopandas as gpd\n",
    "import rasterio.features\n",
    "from shapely.geometry import shape\n",
    "import pandas as pd\n",
    "import os\n",
    "\n",
    "\n",
    "color_mapping = {\n",
    "    'Annual Row Crops': '#f1c41f',\n",
    "    'Hay': '#fff85f',\n",
    "    'Alfalfa': '#93d9d3',\n",
    "    'Other crops': '#ffac00',\n",
    "    'Tree Crops': '#a8df45',\n",
    "    'Barren': '#939973',\n",
    "    'Mixed Forest': '#00aa83',\n",
    "    'Forest': '#4b9f2d',\n",
    "    'Evergreen_Forest': '#00a900',\n",
    "    'Pasture': '#7ff43e',\n",
    "    'Shrub': '#c39251',\n",
    "    'Wetland': '#78992f',\n",
    "    'Developed': '#adadad',\n",
    "    'Fallow': '#8f4f51',\n",
    "    'Other Crops': '#f2aa84',\n",
    "    'Vegetables & Fruits': '#ea5f48',\n",
    "    'Water': '#5d74e9'\n",
    "}\n",
    "\n",
    "font_properties = {\n",
    "    'family': 'Times New Roman',\n",
    "    'style': 'normal', \n",
    "    'weight': 'normal',   \n",
    "    'size': 12         \n",
    "}\n",
    "#Graph Dimensions\n",
    "x_dim, y_dim = 6, 5\n",
    "root_dir = r\"C:\\Users\\twk54\\Documents\\Publications\\Repository\"\n",
    "\n",
    "\n",
    "# This year value selects the CDL to use, if the analysis is for future sites, use the newest available, if it is for past, use 2008\n",
    "gdb_path = f\"{root_dir}/Data/INFEWS_Solar.gpkg\"\n",
    "remap_csv = fr'{root_dir}/Data/Tables/Land_Cover_Catagories.csv'\n",
    "fal_proportions = pd.read_excel(f\"{root_dir}/Data/Tables/Cover_Type_Adjustement(Richardson2022).xlsx\", sheet_name=\"Proportions\")\n",
    "fal_proportions.set_index('Crop', inplace=True)\n",
    "print(fal_proportions.loc[\"Alfalfa\", \"Proportion\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5afeccd",
   "metadata": {},
   "source": [
    "### Remap Cover Type Raster\n",
    "\n",
    "This block reclassifies the Crop Data Layer raster based on the value mappings in \"Land_Cover_Catagories.csv\"\n",
    "\n",
    "| Value | Count  | Class_Name  | Remap | New Classes   | NewID |\n",
    "|-------|--------|-------------|-------|---------------|-------|\n",
    "| 0     | 122662 | Background  | 9     | Annual_Grains | 1     |\n",
    "| 1     | 6665545| Corn        | 10    | Vegetables    | 2     |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f444e00c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import rasterio\n",
    "import numpy as np\n",
    "\n",
    "year = 2008\n",
    "raw_raster_path = f\"{root_dir}/Data/Rasters/Raw/NYS_{year}_CDL_30m.tif\"\n",
    "reclassified_raster_path = f'{root_dir}/Data/Rasters/Reclassified/NYS_{year}_CDL_Reclassed.tif'\n",
    "df = pd.read_csv(remap_csv)\n",
    "\n",
    "def create_mapping(df):\n",
    "    mapping = pd.Series(df['Remap'].values, index=df['Value']).to_dict()\n",
    "    return mapping\n",
    "\n",
    "def remap_raster(raster_path, output_raster_path, mapping, default_value=0):\n",
    "    with rasterio.open(raster_path) as src:\n",
    "        band1 = src.read(1)\n",
    "        \n",
    "        # Determine the smallest data type that can accommodate the range of values\n",
    "        dtype = 'uint8' if max(mapping.values()) <= 255 else 'int16'\n",
    "        \n",
    "        # Prepare the output array with a default value\n",
    "        remapped_array = np.full(band1.shape, default_value, dtype=dtype)\n",
    "        \n",
    "        # Apply the mapping\n",
    "        for orig_value, new_value in mapping.items():\n",
    "            if pd.notna(new_value):  # Only apply mapping if new_value is not NaN\n",
    "                remapped_array[band1 == orig_value] = int(new_value)\n",
    "            else:\n",
    "                print(f\"Warning: No mapping for value {orig_value}, using default {default_value}\")\n",
    "\n",
    "        # Copy the metadata to write the new raster\n",
    "        out_meta = src.meta.copy()\n",
    "        out_meta.update({\n",
    "            'dtype': dtype,  # Pass the string representation directly\n",
    "            'nodata': default_value,\n",
    "            'compress': 'lzw'  # Use LZW compression\n",
    "        })\n",
    "\n",
    "        # Write the new raster using the new values\n",
    "        with rasterio.open(output_raster_path, \"w\", **out_meta) as dest:\n",
    "            dest.write(remapped_array, 1)\n",
    "\n",
    "# Create the value mapping\n",
    "value_mapping = create_mapping(df)\n",
    "\n",
    "rerun =True # Set to false to skip reclassifying raster\n",
    "# Remap the raster values, specify a default value if necessary\n",
    "if not os.path.exists(reclassified_raster_path) or rerun==True:\n",
    "    remap_raster(raw_raster_path, reclassified_raster_path, value_mapping, default_value=0)\n",
    "\n",
    "# Optionally save the remap values to a CSV\n",
    "cover_df = df[['New Classes', 'NewID']].copy().reset_index(drop=True)\n",
    "cover_df.dropna(subset=['New Classes', 'NewID'], inplace=True)\n",
    "cover_df['New ID'] = cover_df['NewID'].astype(int)\n",
    "cover_df = cover_df.drop('NewID', axis=1)\n",
    "cover_df.to_csv(f'{root_dir}/Data/Tables/Outputs/remapsummary.csv', index=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "388ad54d",
   "metadata": {},
   "source": [
    "### Perform Zonal Statistics on Future Projected Sites\n",
    "\n",
    "This cell is a combined calculation and graphing process so that multiple datasets can be looped through.\n",
    "This handles all future scenarios in a single feature class in a GDB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "53d6daa2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['No_Restrictions_SAT', 'NoMSG1_4_SAT', 'NoRowCrops_or_MSG14_SAT']\n",
      "Site scenario combinations that will be graphed: ['No_Restrictions_SAT', 'NoMSG1_4_SAT', 'NoRowCrops_or_MSG14_SAT']\n",
      "No_Restrictions_SAT\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Water                    204.48\n",
       "Shrub                    135.45\n",
       "Wetland                 3934.35\n",
       "Other Crops                0.00\n",
       "Barren                   420.93\n",
       "Fallow                   462.33\n",
       "Vegetables & Fruits      620.10\n",
       "Tree_Crops                 0.00\n",
       "Developed               7380.54\n",
       "Hay                     9291.51\n",
       "Alfalfa                 9761.94\n",
       "Forest                 13605.93\n",
       "Pasture                26875.17\n",
       "Annual Row Crops       29315.52\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No_Restrictions_SAT\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NoMSG1_4_SAT\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Water                     99.90\n",
       "Shrub                    113.94\n",
       "Wetland                 4244.49\n",
       "Other Crops                0.00\n",
       "Barren                   383.94\n",
       "Fallow                   431.55\n",
       "Vegetables & Fruits      344.52\n",
       "Tree_Crops                 0.00\n",
       "Developed               7271.91\n",
       "Hay                    11119.41\n",
       "Alfalfa                 8806.68\n",
       "Forest                 14249.61\n",
       "Pasture                27751.41\n",
       "Annual Row Crops       24482.07\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NoMSG1_4_SAT\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NoRowCrops_or_MSG14_SAT\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Water                    155.97\n",
       "Shrub                    171.99\n",
       "Wetland                 5629.50\n",
       "Other Crops                0.00\n",
       "Barren                   495.27\n",
       "Fallow                   424.17\n",
       "Vegetables & Fruits      666.54\n",
       "Tree_Crops                 0.00\n",
       "Developed              10353.87\n",
       "Hay                    16490.43\n",
       "Alfalfa                  764.64\n",
       "Forest                 20587.95\n",
       "Pasture                42289.65\n",
       "Annual Row Crops         591.30\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NoRowCrops_or_MSG14_SAT\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import rasterio\n",
    "from rasterstats import zonal_stats\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import fiona\n",
    "site_types = ['SAT']#The site types that you would like graphs of. (possible options: 'SAT', 'Lg', 'FA')\n",
    "desired_scenarios = ['No_Restrictions', 'NoMSG1_4', 'NoRowCrops_or_MSG14' ] # The scenarios that you would like to produce graphs of\n",
    "all_combinations = []\n",
    "for type in site_types:\n",
    "    for scenario in desired_scenarios:\n",
    "        combination = f'{scenario}_{type}'\n",
    "        all_combinations.append(combination)\n",
    "print(all_combinations)\n",
    "year = 2023 \n",
    "if year != 2023:\n",
    "    print(\"WARNING! The selected year does not match the expected value for this analysis type, please confirm.\")\n",
    "\n",
    "font_properties = {\n",
    "    'family': 'Times New Roman',\n",
    "    'style': 'normal',\n",
    "    'weight': 'normal',\n",
    "    'size': 12\n",
    "}\n",
    "\n",
    "unit = \"Ha\"  # \"Acres\"\n",
    "cover_df = pd.read_csv(f'{root_dir}/Data/Tables/Outputs/remapsummary.csv')\n",
    "feature_class_name = \"Potential_Future_Sites_new\"\n",
    "layers = fiona.listlayers(gdb_path)\n",
    "color_mapping = {\n",
    "    'Annual Row Crops': '#f1c41f',\n",
    "    'Hay': '#fff85f',\n",
    "    'Alfalfa': '#93d9d3',\n",
    "    'Other crops': '#ffac00',\n",
    "    'Tree Crops': '#a8df45',\n",
    "    'Barren': '#939973',\n",
    "    'Mixed Forest': '#00aa83',\n",
    "    'Forest': '#4b9f2d',\n",
    "    'Evergreen_Forest': '#00a900',\n",
    "    'Pasture': '#7ff43e',\n",
    "    'Shrub': '#c39251',\n",
    "    'Wetland': '#78992f',\n",
    "    'Developed': '#adadad',\n",
    "    'Fallow': '#8f4f51',\n",
    "    'Other Crops': '#f2aa84',\n",
    "    'Vegetables & Fruits': '#ea5f48',\n",
    "    'Water': '#5d74e9',\n",
    "    'All_FAL': '#999999'\n",
    "}\n",
    "\n",
    "\n",
    "print(f'Site scenario combinations that will be graphed: {all_combinations}')\n",
    "\n",
    "polygons = gpd.read_file(gdb_path, layer=feature_class_name)\n",
    "unique_scenarios = polygons[\"Scenario and Type\"].unique()\n",
    "#print(f'All possible scenarios: {unique_scenarios}')\n",
    "raster = rasterio.open(reclassified_raster_path)\n",
    "\n",
    "master_df = pd.DataFrame()\n",
    "\n",
    "for scenario in unique_scenarios:\n",
    "    if scenario not in all_combinations:\n",
    "        continue\n",
    "    sql_query = f'\"Scenario and Type\" = \\'{scenario}\\''\n",
    "    scenario_polygons = gpd.read_file(gdb_path, layer=feature_class_name, where=sql_query)\n",
    "\n",
    "    stats = zonal_stats(scenario_polygons, reclassified_raster_path, stats=\"count\", categorical=True, nodata=raster.nodata)\n",
    "    stats_df = pd.DataFrame(stats).fillna(0)\n",
    "    stats_df.columns = [str(col) for col in stats_df.columns]\n",
    "    stats_df.rename(columns={col: int(col) for col in stats_df.columns if col.isdigit()}, inplace=True)\n",
    "\n",
    "\n",
    "    graph_name = f\"LC_{scenario}\"\n",
    "    cell_size_ha = 900 / 10000\n",
    "\n",
    "    stats_df *= cell_size_ha\n",
    "\n",
    "    rename_dict = cover_df.set_index('New ID')['New Classes'].to_dict()\n",
    "    stats_df.rename(columns=rename_dict, inplace=True)\n",
    "\n",
    "    scenario_polygons = scenario_polygons.join(stats_df, rsuffix='_zonal')\n",
    "    graph_path = f'{root_dir}/Outputs/Figures/{graph_name}.jpg'\n",
    "    polygons_df = scenario_polygons\n",
    "    valid_cover_types = cover_df['New Classes'].tolist()\n",
    "    filtered_columns = [col for col in polygons_df.columns if col in valid_cover_types]\n",
    "    area_sums = polygons_df[filtered_columns].sum().fillna(0)\n",
    "    area_sums.index = [idx.replace('_zonal', '') for idx in area_sums.index]\n",
    "    area_sums = area_sums.sort_values()\n",
    "\n",
    "    order = ['Water', 'Shrub', 'Wetland', 'Other Crops', 'Barren', 'Fallow', 'Vegetables & Fruits', 'Tree_Crops', 'Developed', 'Hay', 'Alfalfa', 'Forest', 'Pasture', 'Annual Row Crops']\n",
    "    ordered_area_sums = area_sums.reindex(order).fillna(0)\n",
    "    print(scenario)\n",
    "    display(ordered_area_sums)\n",
    "\n",
    "    ordered_area_sums['Alfalfa_FAL'] = ordered_area_sums['Alfalfa'] * fal_proportions.loc[\"Alfalfa\", \"Proportion\"]\n",
    "    ordered_area_sums['Row Crops_FAL'] = ordered_area_sums['Annual Row Crops'] * fal_proportions.loc[\"Row Crops\", \"Proportion\"]\n",
    "    ordered_area_sums['Hay_FAL'] = ordered_area_sums['Hay'] * fal_proportions.loc[\"Hay\", \"Proportion\"]\n",
    "    ordered_area_sums['Tree Crops_FAL'] = ordered_area_sums['Tree_Crops'] * fal_proportions.loc[\"Tree Crops\", \"Proportion\"]\n",
    "    ordered_area_sums['Pasture_FAL'] = ordered_area_sums['Pasture'] * fal_proportions.loc[\"Pasture\", \"Proportion\"]\n",
    "    ordered_area_sums['Fallow_FAL'] = ordered_area_sums['Fallow'] * fal_proportions.loc[\"Fallow\", \"Proportion\"]\n",
    "    ordered_area_sums['All FAL'] = (\n",
    "        ordered_area_sums['Alfalfa_FAL'] +\n",
    "        ordered_area_sums['Row Crops_FAL'] +\n",
    "        ordered_area_sums['Hay_FAL'] +\n",
    "        ordered_area_sums['Tree Crops_FAL'] +\n",
    "        ordered_area_sums['Pasture_FAL'] +\n",
    "        ordered_area_sums['Fallow_FAL']\n",
    "    )\n",
    "\n",
    "    graph_data = ordered_area_sums[~ordered_area_sums.index.str.endswith('_FAL') | (ordered_area_sums.index == 'All FAL')]\n",
    "    graph_data_sorted = graph_data.drop(labels='All FAL', errors='ignore').sort_values()\n",
    "    if 'All FAL' in graph_data.index:\n",
    "        graph_data_sorted = pd.concat([graph_data_sorted, graph_data.loc[['All FAL']]])\n",
    "\n",
    "    total_area = graph_data_sorted.sum()\n",
    "    graph_data_percent = (graph_data_sorted / total_area) * 100\n",
    "\n",
    "    colors = [color_mapping.get(idx, '#000000') for idx in graph_data_percent.index]\n",
    "    if not all(colors):\n",
    "        raise ValueError(f\"Color assignment failed. Some cover types might not have valid colors: {colors}\")\n",
    "    print(scenario)\n",
    "    plt.figure(figsize=(x_dim, y_dim))\n",
    "    graph_data_percent.plot(kind='bar', color=colors, width=0.89)\n",
    "\n",
    "    plt.xlabel('Cover Type', fontdict=font_properties)\n",
    "    plt.ylabel('Percent of Area', fontdict=font_properties)\n",
    "    plt.xticks(rotation=30, ha='right', fontproperties=font_properties)\n",
    "    plt.ylim(0, 40)\n",
    "\n",
    "    for i, value in enumerate(graph_data_percent):\n",
    "        plt.text(i, value + 1, f'{value:.0f}%', ha='center', va='bottom', fontproperties=font_properties)\n",
    "\n",
    "    plt.savefig(graph_path, dpi=300, format='jpg', bbox_inches='tight')\n",
    "    plt.show()\n",
    "    plt.close()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b94cc92",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "5bcd9050",
   "metadata": {},
   "source": [
    "### Merge Into Panel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c7a0a82f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image, ImageDraw, ImageFont\n",
    "import sys\n",
    "import os\n",
    "\n",
    "site_type = \"SAT\"\n",
    "figures_path = f'{root_dir}/Outputs/Figures'\n",
    "# Dictionary to map scenario keys with plain text\n",
    "selected = {\n",
    "    f'LC_No_Restrictions_{site_type}': 'No Restrictions',\n",
    "    f'LC_NoMSG1_4_{site_type}': 'No High Quality Ag Land \\n(MSG 1-4)',\n",
    "    f'LC_NoRowCrops_or_MSG14_{site_type}': 'No Row Crops or \\nMSG 1-4'\n",
    "    \n",
    "}\n",
    "\n",
    "\n",
    "\n",
    "image_paths = []\n",
    "for combination in all_combinations:\n",
    "    image_paths.append(f'{figures_path}/LC_{combination}.jpg')\n",
    "\n",
    "def merge_images(image_paths, text_labels, output_path):\n",
    "    if len(image_paths) != 3:\n",
    "        raise ValueError(\"The number of images must be exactly 3 for a vertical panel.\")\n",
    "\n",
    "    # Open all images\n",
    "    images = [Image.open(path) for path in image_paths]\n",
    "\n",
    "    # Determine the max width and height\n",
    "    max_width = max(image.width for image in images)\n",
    "    max_height = max(image.height for image in images)\n",
    "\n",
    "    # Resize images by adding white padding\n",
    "    padded_images = []\n",
    "    for image in images:\n",
    "        new_image = Image.new('RGB', (max_width, max_height), (255, 255, 255))\n",
    "        new_image.paste(image, ((max_width - image.width) // 2, (max_height - image.height) // 2))\n",
    "        padded_images.append(new_image)\n",
    "\n",
    "    # Load font\n",
    "    font_path = os.path.join(root_dir, \"msc\", \"Times New Roman.ttf\")\n",
    "    font_size = 105  # Adjust size as needed\n",
    "    font = ImageFont.truetype(font_path, font_size)\n",
    "\n",
    "    # Add text to each image\n",
    "    for image, text in zip(padded_images, text_labels):\n",
    "        draw = ImageDraw.Draw(image)\n",
    "        text_x = max_width // 5 #- font.getlength(text) // 2\n",
    "        text_y = max_height - 1400  # Position text below image\n",
    "        draw.text((text_x, text_y), text, fill=\"black\", font=font)\n",
    "\n",
    "    # Create the final stacked image\n",
    "    total_width = max_width\n",
    "    total_height = 3 * max_height\n",
    "\n",
    "    merged_image = Image.new('RGB', (total_width, total_height), (255, 255, 255))\n",
    "\n",
    "    # Paste images onto the final canvas\n",
    "    for i, image in enumerate(padded_images):\n",
    "        merged_image.paste(image, (0, i * max_height))\n",
    "\n",
    "    # Save the merged image\n",
    "    merged_image.save(output_path)\n",
    "\n",
    "\n",
    "text_labels = list(selected.values())\n",
    "output_path = f'{figures_path}/LC_{site_type}_Vertical_Panel.jpg'\n",
    "merge_images(image_paths, text_labels, output_path)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5354895b",
   "metadata": {},
   "source": [
    "### Land Cover Intersection for Existing sites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1aa98faa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NoRowCrops_or_MSG14_Large\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Water                    0.63\n",
       "Shrub                   29.43\n",
       "Wetland                 46.26\n",
       "Other Crops              0.00\n",
       "Barren                  26.01\n",
       "Fallow                 126.99\n",
       "Vegetables & Fruits      4.59\n",
       "Tree_Crops               0.00\n",
       "Developed              192.15\n",
       "Hay                    827.46\n",
       "Alfalfa                333.27\n",
       "Forest                 488.43\n",
       "Pasture                714.42\n",
       "Annual Row Crops       863.82\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "year = 2008\n",
    "reclassified_raster_path = f'{root_dir}/Data/Rasters/Reclassified/NYS_{year}_CDL_Reclassed.tif'\n",
    "font_properties = {\n",
    "    'family': 'Times New Roman',\n",
    "    'style': 'normal',\n",
    "    'weight': 'normal',\n",
    "    'size': 12\n",
    "}\n",
    "\n",
    "unit = \"Ha\"  # \"Acres\"\n",
    "cover_df = pd.read_csv(fr\"C:\\Users\\twk54\\Desktop\\Projects\\INFEWS_Solar\\Tables\\temp\\remapvalues.csv\")\n",
    "feature_class_name = \"Detected_Sites\"\n",
    "layers = fiona.listlayers(gdb_path)\n",
    "color_mapping = {\n",
    "    'Annual Row Crops': '#f1c41f',\n",
    "    'Hay': '#fff85f',\n",
    "    'Alfalfa': '#93d9d3',\n",
    "    'Other crops': '#ffac00',\n",
    "    'Tree Crops': '#a8df45',\n",
    "    'Barren': '#939973',\n",
    "    'Mixed Forest': '#00aa83',\n",
    "    'Forest': '#4b9f2d',\n",
    "    'Evergreen_Forest': '#00a900',\n",
    "    'Pasture': '#7ff43e',\n",
    "    'Shrub': '#c39251',\n",
    "    'Wetland': '#78992f',\n",
    "    'Developed': '#adadad',\n",
    "    'Fallow': '#8f4f51',\n",
    "    'Other Crops': '#f2aa84',\n",
    "    'Vegetables & Fruits': '#ea5f48',\n",
    "    'Water': '#5d74e9',\n",
    "    'All_FAL': '#999999'\n",
    "}\n",
    "\n",
    "polygons = gpd.read_file(gdb_path, layer=feature_class_name)\n",
    "\n",
    "raster = rasterio.open(f'{root_dir}/Data/Rasters/Reclassified/NYS_{year}_CDL_Reclassed.tif')\n",
    "\n",
    "master_df = pd.DataFrame()\n",
    "\n",
    "stats = zonal_stats(polygons, reclassified_raster_path, stats=\"count\", categorical=True, nodata=raster.nodata)\n",
    "stats_df = pd.DataFrame(stats).fillna(0)\n",
    "stats_df.columns = [str(col) for col in stats_df.columns]\n",
    "stats_df.rename(columns={col: int(col) for col in stats_df.columns if col.isdigit()}, inplace=True)\n",
    "\n",
    "\n",
    "graph_name = f\"LC_Existing_sites_{year}\"\n",
    "cell_size_ha = 900 / 10000\n",
    "\n",
    "stats_df *= cell_size_ha\n",
    "\n",
    "rename_dict = cover_df.set_index('New ID')['New Classes'].to_dict()\n",
    "stats_df.rename(columns=rename_dict, inplace=True)\n",
    "\n",
    "scenario_polygons = polygons.join(stats_df, rsuffix='_zonal')\n",
    "graph_path = fr'{root_dir}/Outputs/Figures/{graph_name}.jpg'\n",
    "polygons_df = scenario_polygons\n",
    "valid_cover_types = cover_df['New Classes'].tolist()\n",
    "filtered_columns = [col for col in polygons_df.columns if col in valid_cover_types]\n",
    "area_sums = polygons_df[filtered_columns].sum().fillna(0)\n",
    "area_sums.index = [idx.replace('_zonal', '') for idx in area_sums.index]\n",
    "area_sums = area_sums.sort_values()\n",
    "\n",
    "order = ['Water', 'Shrub', 'Wetland', 'Other Crops', 'Barren', 'Fallow', 'Vegetables & Fruits', 'Tree_Crops', 'Developed', 'Hay', 'Alfalfa', 'Forest', 'Pasture', 'Annual Row Crops']\n",
    "ordered_area_sums = area_sums.reindex(order).fillna(0)\n",
    "print(scenario)\n",
    "display(ordered_area_sums)\n",
    "\n",
    "ordered_area_sums['Alfalfa_FAL'] = ordered_area_sums['Alfalfa'] * fal_proportions.loc[\"Alfalfa\", \"Proportion\"]\n",
    "ordered_area_sums['Row Crops_FAL'] = ordered_area_sums['Annual Row Crops'] * fal_proportions.loc[\"Row Crops\", \"Proportion\"]\n",
    "ordered_area_sums['Hay_FAL'] = ordered_area_sums['Hay'] * fal_proportions.loc[\"Hay\", \"Proportion\"]\n",
    "ordered_area_sums['Tree Crops_FAL'] = ordered_area_sums['Tree_Crops'] * fal_proportions.loc[\"Tree Crops\", \"Proportion\"]\n",
    "ordered_area_sums['Pasture_FAL'] = ordered_area_sums['Pasture'] * fal_proportions.loc[\"Pasture\", \"Proportion\"]\n",
    "ordered_area_sums['Fallow_FAL'] = ordered_area_sums['Fallow'] * fal_proportions.loc[\"Fallow\", \"Proportion\"]\n",
    "ordered_area_sums['All FAL'] = (\n",
    "    ordered_area_sums['Alfalfa_FAL'] +\n",
    "    ordered_area_sums['Row Crops_FAL'] +\n",
    "    ordered_area_sums['Hay_FAL'] +\n",
    "    ordered_area_sums['Tree Crops_FAL'] +\n",
    "    ordered_area_sums['Pasture_FAL'] +\n",
    "    ordered_area_sums['Fallow_FAL']\n",
    ")\n",
    "\n",
    "graph_data = ordered_area_sums[~ordered_area_sums.index.str.endswith('_FAL') | (ordered_area_sums.index == 'All FAL')]\n",
    "graph_data_sorted = graph_data.drop(labels='All FAL', errors='ignore').sort_values()\n",
    "if 'All FAL' in graph_data.index:\n",
    "    graph_data_sorted = pd.concat([graph_data_sorted, graph_data.loc[['All FAL']]])\n",
    "\n",
    "total_area = graph_data_sorted.sum()\n",
    "graph_data_percent = (graph_data_sorted / total_area) * 100\n",
    "\n",
    "colors = [color_mapping.get(idx, '#000000') for idx in graph_data_percent.index]\n",
    "if not all(colors):\n",
    "    raise ValueError(f\"Color assignment failed. Some cover types might not have valid colors: {colors}\")\n",
    "\n",
    "plt.figure(figsize=(x_dim, y_dim))\n",
    "graph_data_percent.plot(kind='bar', color=colors, width=0.89)\n",
    "\n",
    "plt.xlabel('Cover Type', fontdict=font_properties)\n",
    "plt.ylabel('Percent of Area', fontdict=font_properties)\n",
    "plt.xticks(rotation=30, ha='right', fontproperties=font_properties)\n",
    "plt.ylim(0, 25)\n",
    "\n",
    "for i, value in enumerate(graph_data_percent):\n",
    "    plt.text(i, value + 1, f'{value:.0f}%', ha='center', va='bottom', fontproperties=font_properties)\n",
    "\n",
    "plt.savefig(graph_path, dpi=300, format='jpg', bbox_inches='tight')\n",
    "plt.show()\n",
    "plt.close()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e15adf07",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
